Objective To investigate whether prostate-specific antigen (PSA) fluctuation correlates with a prostate cancer and to assess whether PSA fluctuation could be used for diagnosis of prostate cancer. Materials and Methods Our study included 229 patients who were performed a prostate biopsy (non-cancer group, 177; prostate cancer group, 52). Enrolled patients were provided twice PSA tests within 6 months. PSA fluctuation (%/month) was defined as a change rate of PSA per a month. Independent t test was used to compare between two groups. Receiver operator characteristic curve was used to assess the availability as a differential diagnostic tool and the correlation. Simple linear regression was performed to analyze a correlation between PSA fluctuation and other factors such as age, PSA, PSA density, and prostate volume. Results There were significant differences in PSA, PSA density, percentage of free PSA, and PSA fluctuation between two groups. PSA fluctuation was significantly greater in non-cancer group than prostate cancer group (19.95±23.34%/month vs 9.63±8.57%/month, P=0.004). The most optimal cut-off value of PSA fluctuation was defined as 8.48%/month (sensitivity, 61.6%; specificity, 59.6%; AUC, 0.633; P=0.004). In a simple linear regression model, only PSA level was significantly correlated with PSA fluctuation. Conclusion Patients with wide PSA fluctuations, although baseline PSA levels are high, might have a low risk of diagnosis with prostate cancer. Thus, serial PSA measurements could be an option in patients with an elevated PSA level.

PURPOSE: Preexisting bone loss in men with prostate cancer is an important issue due to the accelerated bone loss during androgen deprivation therapy (ADT). In addition, a high prostate-specific antigen (PSA) level has been reported to be related to bone metabolism. This study assessed the factors associated with osteoporosis in Korean men with non-metastatic prostate cancer before undergoing ADT. MATERIAL AND METHODS: The study enrolled patients admitted for a prostate biopsy because of a high PSA or palpable nodule on a digital rectal examination. We divided the patients (n = 172) according to the results of the biopsy: group I, non-metastatic prostate cancer (n = 42) and group II, benign prostatic hypertrophy (BPH; n = 130). The lumbar bone mineral density (BMD) was evaluated using quantitative computed tomography. The demographic, health status, lifestyle, body mass index (BMI), serum testosterone concentration, and disease variables in prostate cancer (Gleason score, clinical stage, and PSA) were analyzed prospectively to determine their effect on the BMD. RESULTS: The estimated mean T-score was higher in group I than in group II (-1.96 ± 3.35 vs. -2.66 ± 3.20), but without statistic significance (p = 0.235). The significant factors correlated with BMD in group I were a high serum PSA (ß = -0.346, p = 0.010) and low BMI (ß = 0.345, p = 0.014) in the multiple linear regression model. Also old age (r = -0.481, p = 0.001), a high serum PSA (r = -0.571, p < 0.001), low BMI (r = 0.598, p < 0.001), and a high Gleason’s score (r = -0.319, p = 0.040) were the factors related to BMD in the correlation. The significant factors correlated with BMD in group II were old age (ß = -0.324, p = 0.001) and BMI (ß = 0.143, p = 0.014) in the multiple linear regression model. CONCLUSIONS: The risk factors for osteoporosis in men with prostate cancer include a low BMI, and elevated serum PSA. Monitoring BMD from the outset of ADT is a logical first step in the clinical strategy to avoid or minimize potential bone-related complications in these patients.